binCI {FSA} R Documentation

## Confidence intervals for binomial probability of success.

### Description

Uses one of three methods to compute a confidence interval for the probability of success (p) in a binomial distribution.

### Usage

```binCI(
x,
n,
conf.level = 0.95,
type = c("wilson", "exact", "asymptotic"),
verbose = FALSE
)
```

### Arguments

 `x` A single or vector of numbers that contains the number of observed successes. `n` A single or vector of numbers that contains the sample size. `conf.level` A single number that indicates the level of confidence (default is `0.95`). `type` A string that identifies the type of method to use for the calculations. See details. `verbose` A logical that indicates whether `x`, `n`, and `x/n` should be included in the returned matrix (`=TRUE`) or not (`=FALSE`; DEFAULT).

### Details

This function will compute confidence interval for three possible methods chosen with the `type` argument.

 `type="wilson"` Wilson's (Journal of the American Statistical Association, 1927) confidence interval for a proportion. This is the score CI, based on inverting the asymptotic normal test using the null standard error. `type="exact"` Computes the Clopper/Pearson exact CI for a binomial success probability. `type="asymptotic"` This uses the normal distribution approximation.

Note that Agresti and Coull (2000) suggest that the Wilson interval is the preferred method and is, thus, the default `type`.

### Value

A #x2 matrix that contains the lower and upper confidence interval bounds as columns and, if `verbose=TRUE` `x`, `n`, and `x/n` .

### Note

This is primarily a wrapper function for `binom.exact`, `binom.wilson`, and `binom.approx` (documented in `binom.conf.int`) from the epitools package.

### Author(s)

Derek H. Ogle, derek@derekogle.com

### References

Agresti, A. and B.A. Coull. 1998. Approximate is better than “exact” for interval estimation of binomial proportions. American Statistician, 52:119-126.

See `binom.test`; `binconf` in Hmisc; `binom.exact`, `binom.wilson`, and `binom.approx` documented in `binom.conf.int` in epitools, and functions in binom.

### Examples

```## All types at once
binCI(7,20)

## Individual types
binCI(7,20,type="wilson")
binCI(7,20,type="exact")
binCI(7,20,type="asymptotic")
binCI(7,20,type="asymptotic",verbose=TRUE)

## Multiple types
binCI(7,20,type=c("exact","asymptotic"))
binCI(7,20,type=c("exact","asymptotic"),verbose=TRUE)

## Use with multiple inputs
binCI(c(7,10),c(20,30),type="wilson")
binCI(c(7,10),c(20,30),type="wilson",verbose=TRUE)

```

[Package FSA version 0.8.26.9000 Index]